Vedat Verter

Multi-period reverse logistics network design

The configuration of the reverse logistics network is a complex problem comprising the determination of the optimal sites and capacities of collection centers, inspection centers, remanufacturing facilities, and/or recycling plants. In this paper, we propose a profit maximization modeling framework for reverse logistics network design problems. We present a mixed-integer linear programming formulation that is flexible to incorporate most of the reverse network structures plausible in practice. In order to consider the possibility of making future adjustments in the network configuration to allow gradual changes in the network structure and in the capacities of the facilities, we consider a multi-period setting. We propose a multi-commodity formulation and use a reverse bill of materials in order to capture component commonality among different products and to have the flexibility to incorporate all plausible means in tackling product returns. The proposed general framework is justified by a case study in the context of reverse logistics network design for washing machines and tumble dryers in Germany. We conduct extensive parametric and scenario analysis to illustrate the potential benefits of using a dynamic model as opposed to its static counterpart, and also to derive a number of managerial insights.

The effect of categorizing returned products in remanufacturing

An increasing number of companies have been implementing comprehensive recycling and remanufacturing programs. These endeavors typically involve the operation of joint manufacturing and remanufacturing systems. One of the major challenges in managing such hybrid systems is the stochastic nature of product returns. In particular, there is significant variability in the condition of the returns. This paper presents an approach for assessing the impact of quality-based categorization of returned products. Through extensive numerical studies on a continuous-time Markov chain model, we show that incorporation of returned product quality in the remanufacturing and disposal decisions can lead to significant cost savings. We find that these savings are amplified as the return quality decreases, and as the return rate increases. We also show that prioritizing higher quality returns in remanufacturing is, in general, a better strategy.

Location of Preventive Health Care Facilities

This paper is focused on the problem of locating preventive health care facilities. The aim is to maximize participation to prevention programs. We assume that distance is a major determinant of participation and people would go to the closest facility for preventive health care. Each facility is required to have more than a predetermined number of clients because of the direct relationship between volume and quality of preventive services. We provide a mathematical formulation and present alternative solution approaches for this new location problem. We report on computational performance of the proposed methods in locating public health centers in Fulton County, Georgia and mammography screening centers in Montreal, Quebec.

A continuous model for production-distribution system design

Abstract The production–distribution system design problem (PDSDP) involves decisions concerning the structure of a firms supply chain. An overwhelming majority of the literature uses mixed integer programming formulations in representing such facility design decisions. In this paper, we present an alternative modeling framework, which is based on the use of continuous functions to represent spatial distributions of cost and customer demand. The proposed continuous model allows the derivation of a number of insights about the impact of problem parameters on facility design decisions. It is proposed that discrete and continuous modeling approaches complement each other.

Retail-collection network design under deposit-refund

Abstract This paper studies the interplay between industrial firms and government concerning the collection of used products from households. The focus is on the use of a deposit–refund requirement by the government when the collection rate voluntarily achieved by the firms is deemed insufficient. We present a continuous modeling framework for designing a drop-off facility network and determining the sales price that maximize the firms profit under a given deposit–refund. The customers’ preferences with regards to purchasing and returning the product are incorporated via a discrete choice model with stochastic utilities. Through parametric analyses, we determine the net value that can be recovered from a returned product as a key driver for the firm to voluntarily engage in collection. We show that a minimum deposit–refund requirement would not achieve high collection rates for products with low return value and point out two complementary policy tools that can be used by the government.

Incorporating congestion in preventive healthcare facility network design

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The level of participation to preventive healthcare programs is a crucial factor in terms of their effectiveness and efficiency. This paper provides a methodology for designing a network of preventive healthcare facilities so as to maximize participation. The number of facilities to be established and the location of each facility are the main determinants of the configuration of a healthcare facility network. We use the total (travel, waiting and service) time required for receiving the preventive service as a proxy for accessibility of a healthcare facility, and assume that each client would seek the services of the facility with minimum expected total time. At each facility, which we model as an M/M/1 queue so as to capture the level of congestion, the expected number of participants from each population zone decreases with the expected total time. In order to ensure service quality, the facilities cannot be operated unless their level of activity exceeds a minimum workload requirement. The arising mathematical formulation is highly nonlinear, and hence we provide a heuristic solution framework for this problem. Four heuristics are compared in terms of accuracy and computational requirements. The most efficient heuristic is utilized in solving a real life problem that involves the breast cancer screening center network in Montreal. In the context of this case, we found out that centralizing the total system capacity at the locations preferred by clients is a more effective strategy than decentralization by the use of a larger number of smaller facilities. We also show that the proposed methodology can be used in making the investment trade-off between expanding the total system capacity and changing the behavior of potential clients toward preventive healthcare programs by advertisement and education.

Accurate calculation of hazardous materials transport risks

We propose two path-selection algorithms for the transport of hazardous materials. The algorithms can deal with link impedances that are path-dependent. This approach is superior to the use of a standard shortest path algorithm, common in the literature and practice, which results in inaccuracies.

A lead-time based approach for planning rail–truck intermodal transportation of dangerous goods

The remarkable growth in intermodal transportation over the past two decades has not been matched by a comparable level of academic activity, especially in the context of transporting hazardous materials (hazmats). In this paper, we present a first attempt for the development of an analytical framework for planning rail-truck intermodal transportation of hazmats. A bi-objective optimization model to plan and manage intermodal shipments is developed. To represent the current practice, the routing decisions in the model are driven by the delivery-times specified by the customers. An iterative decomposition based solution methodology which takes advantage of the problem structure is provided. A realistic problem instance based on the intermodal service network in eastern US is solved. This framework is used for developing a number of managerial insights, and for generating elements of the risk-cost frontier.

Designing emergency response networks for hazardous materials transportation

Undesirable consequences of dangerous goods incidents can be mitigated by quick arrival of specialized response teams at the accident site. We present a novel methodology to determine the optimal design of a specialized team network so as to maximize its ability to respond to such incidents in a region. We show that this problem can be represented via a maximal arc-covering model. We discuss two formulations for the maximal arc-covering problem, a known one and a new one. Through computational experiments, we establish that the known formulation has excessive computational requirements for large-scale problems, whereas the alternative model constitutes a basis for an efficient heuristic. The methodology is applied to assess the emergency response capability to transport incidents, that involve gasoline, in Quebec and Ontario. We point out the possibility of a significant improvement via relocation of the existing specialized teams, which are currently stationed at the shipment origins.

Chapter 9 Hazardous Materials Transportation

Publisher Summary According to the US Department of Transportation (US DOT), a hazardous material is defined as any substance or material capable of causing harm to people, property, and the environment. Dependence on hazardous materials is a fact in industrialized societies. There are thousands of different hazardous materials in use currently. The United Nations sorts hazardous materials into nine classes according to their physical, chemical, and nuclear properties: explosives and pyrotechnics; gasses; flammable and combustible liquids; flammable, combustible, and dangerous-when-wet solids; oxidizers and organic peroxides; poisonous and infectious materials; radioactive materials; corrosive materials (acidic or basic); and miscellaneous dangerous goods, such as hazardous wastes. In almost all instances, hazmats originate at a location other than their destination. The transportation of hazmats can be classified according to the mode of transport—namely, road, rail, water, air, and pipeline. Some shipments are intermodal; they are switched from one mode to another during transit.